Analisis Perbandingan Rule Pakar dan Decision Tree J48 Dalam Menentukan Jumlah Produksi Kain Tenun Menggunakan Metode Fuzzy Tsukamoto - Tundo Amri Mujahid; Enny itje Sela (STMIK Budi Darma, 2019)
This study explains the comparative analysis of expert rules and J48 decision tree using Tsukamoto fuzzy in determining the amount of woven fabric production. From the results of the research analysis, it was found that the rule base model in this study was a decision tree with 83.3333% accuracy based on the J48 decision tree algorithm that was tested using WEKA tools. The results of direct comparison analysis with actual production data that J48 decision tree rule is the closest to the actual data is with an error rate of 3.89% so that the accuracy of the truth reaches 96.11%, while using expert rules has an error rate of 14.45% so that the accuracy truth obtained reached 85.55%. Therefore, an idea was found that to make a rule without having to consult with experts, that is enough to use a decision tree with WEKA tools, because WEKA tools will display the accuracy of the truth of the rules formed.